Official Press Release
Based on a unique combination of coronary and liver machine learning algorithms, Zebra Medical Vision has developed a technique that helps physicians predict and even prevent the burst of cardiovascular events.
Shefayim, Israel August, 2016 – Zebra Medical Vision, the deep learning imaging analytics company, is announcing two new software algorithms that automatically quantify the amount of calcified plaque in coronary arteries and detect presence of fatty liver in patients’ CT scans. Individually, the algorithms inform caregivers about the cardiovascular and metabolic state of their patients, and together they provide even stronger predictors for risk of heart attack and stroke.
Cardiovascular disease is one of the leading causes of heart attack and stroke – it is responsible for nearly 500,000 deaths every year in the US alone. Calcium which builds up in the walls of the arteries that supply our heart muscle can be seen and quantified on routine CT scans of the chest; the amount of calcification (the coronary calcium score) is a strong predictor for cardiovascular events such as heart attack or strokes.
Fatty liver is also a common condition which affects up to 11% of the population and is increasingly prevalent. Research has shown that the presence of fatty liver is a strong indicator of metabolic changes which are seen in people who have or come to develop insulin resistant diabetes. Fatty liver (also known as non-alcoholic steatohepatitis or NASH) is a preventable cause of chronic liver disease, cirrhosis and liver cancer.
Applying either of these tools independently can greatly assist physicians in early identification of these treatable conditions – but recent research shows that the presence of fatty liver indicates a 2x-4x risk of having high-risk coronary artery plaque and experiencing heart attack and cardiac death.
By applying these algorithms to their patients’ routinely acquired CT scans, caregivers can identify high risk patients earlier, using one or both of these important indicators. In addition, self-insured large employers or insurance companies can better assess risk using existing imaging data. Despite the prevalence of these conditions, both fatty liver and cardiovascular disease are still under diagnosed. Timely recognition should prompt lifestyle and therapeutic interventions aimed to increase well-being and decrease risk of illness.
“This is yet another step in our mission to help provide faster, more accurate radiology services at lower cost, by teaching software to read and identify key clinical conditions in imaging,” said Elad Benjamin, Zebra’s CEO. “We believe that these tools, as well as new algorithms which we continuously release, will help Radiologists deal with the continuous pressure they face to increase output and maintain high quality of care.”
On track to create one hundred new insights in the next three years, Zebra has already secured partnerships with Dell Services and has received financial backing from Intermountain Healthcare, one of the leading healthcare organizations in the US. Zebra continues to expand its relationships and work with ACOs, HMOs and other payors and providers seeking to improve care at lower cost through the power of analytics, predictive modeling and preventative care.
Elad Benjamin - Co-founder and CEO
Eyal Gura - Co-Founder and Chairman of the Board